Ai Enabled Full Stack Developer Experienced in United States

About the Team The Finance Platform & Technology team at OpenAI builds and scales the future-proof systems and data architecture that power our core financial operations. We enable business agility, compliance, and operational excellence across quote-to-cash, procure-to-pay, inventory, and asset management for both B2B and B2C. Our focus is on modernizing workflows through strategic integrations, scalable automation, and seamless data flows empowering smarter decisions, reliable reporting, and sustainable growth as OpenAI evolves About the Role We are looking for a Supply Chain Transformation Architect to redesign and modernize our end-to-end supply chain operations supporting robotics, consumer hardware, and data center infrastructure. This role sits at the intersection of process, systems, and data. Your primary focus will be transforming supply chain processes across planning, procurement, manufacturing, logistics, and fulfillment—then enabling those processes with the right systems architecture, data foundation, and AI-driven automation. You will help move the organization from manual, reactive operations to intelligent, data-driven supply chain execution. In this role you will: Lead End-to-End Supply Chain Transformation Evaluate and redesign core supply chain processes across demand planning, supply planning, procurement, manufacturing operations, logistics, and fulfillment. Identify operational bottlenecks, fragmented workflows, and manual processes that limit scalability. Build standardized process frameworks and operating models that support rapid scaling of hardware programs. Drive Operational Excellence Implement structured supply chain practices such as: S&OP / Integrated Business Planning Supply risk management Inventory optimization Supplier collaboration frameworks Logistics visibility and execution models Establish operational KPIs and governance to improve predictability, responsiveness, and resilience. Architect the Digital Supply Chain Tra

About the Team Equity Administration at OpenAI is responsible for the operational foundation of our equity programs. Our team ensures equity data and reporting are reliable, our systems and integrations are resilient, and our processes and controls are built to scale globally. We work cross-functionally with Legal, Finance/Accounting, Payroll, Tax, People, and key vendors to uphold compliance requirements and enable equity strategy as the company evolves. About the Role We’re looking for an experienced Manager, Global Equity Administration to help run our global equity programs with a focus on high-quality execution, scalable processes, auditable controls, and reliable equity systems. You will be hands-on in day-to-day equity administration and help improve how we operate as we scale. You will report to the Head of Equity Administration and partner closely with Legal, Equity Programs, Compensation, Tax, Payroll, and Finance to ensure equity operations are accurate, timely, and employee-friendly. Location: This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Execute end-to-end employee equity administration across key lifecycle events (new grants, vesting/RSU releases, option exercises, and related transactions). Run recurring operational cycles by managing timelines, checklists, stakeholder inputs, and issue resolution. Produce audit-ready equity reporting and support accounting, compliance, and reporting needs with accurate, well-documented data. Build and maintain automated reporting (scheduled reports, dashboards, reconciliations) to reduce manual effort and improve speed and accuracy. Support equity system operations (Shareworks or comparable) including troubleshooting, configuration updates, permissions, report builds, and workflow maintenance. Partner with Internal Controls to keep process documentation, narratives, and flowcharts current,

About the Team The Foundations Research team works on high-risk, high-reward ideas that could shape the next decade of AI. Our goal is to advance the science and data that enable our training and scaling efforts, with a particular focus on future frontier models. Pushing the boundaries of data, scaling laws, optimization techniques, model architectures, and efficiency improvements to propel our science. The Search team sits within Foundations, building agentic search by co-designing model–system interfaces with the core search stack (serving, indexing, retrieval) to translate model intent into reliable, real-world actions. Operating at the frontier of AI and information retrieval, the team develops large-scale systems that transform and index vast corpora, enabling models to reason over global knowledge and act dependably. In close partnership with researchers, we rapidly bring modeling breakthroughs into production and redefine how intelligent systems discover, retrieve, and synthesize information at planetary scale. About the Role We’re looking for a researcher focused on our embedding retrieval efforts. You’ll work with a a team of world-class research scientists and engineers developing foundational technology that enables models to retrieve and condition on the right information, at the right time. This includes designing new embedding training objectives, scalable vector store architectures, and dynamic indexing methods. This work will support retrieval across many OpenAI products and internal research efforts, with opportunities for scientific publication and deep technical impact. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. Responsibilities Tackle embedding models and retrieval systems optimized for grounding, relevance, and adaptive reasoning. Collaborate with a team of researchers and engineers building end-to-end infrastructure for training, evaluati

About the Team Training Runtime designs the core distributed machine-learning training runtime that powers everything from early research experiments to frontier-scale model runs. With a dual mandate to accelerate researchers and enable frontier scale, we’re building a unified, modular runtime that meets researchers where they are and moves with them up the scaling curve. Our work focuses on three pillars: high-performance, asynchronous, zero-copy tensor and optimizer-state-aware data movement; performant, high-uptime, fault-tolerant training frameworks (training loop, state management, resilient checkpointing, deterministic orchestration, and observability); and distributed process management for long-lived, job-specific and user-provided processes. We integrate proven large-scale capabilities into a composable, developer-facing runtime so teams can iterate quickly and run reliably at any scale, partnering closely with model-stack, research, and platform teams. Success for us is measured by raising both training throughput (how fast models train) and researcher throughput (how fast ideas become experiments and products). About the Role As a Training Performance Engineer, you’ll drive efficiency improvements across our distributed training stack. You’ll analyze large-scale training runs, identify utilization gaps, and design optimizations that push the boundaries of throughput and uptime. This role blends deep systems understanding with practical performance engineering — analyzing GPU kernel performance, collective communication throughput, investigating I/O bottlenecks, and sharding our models so we can train them at massive scale. You’ll help ensure that our clusters are running at peak performance, enabling OpenAI to train larger, more capable models with the same compute budget. This role is based in San Francisco, CA. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees. In this role, you will: Profil

About OpenAI OpenAI is dedicated to ensuring that artificial general intelligence (AGI) benefits all of humanity. Our mission requires building not only world-class AI models, but also the infrastructure that enables those models to be deployed reliably, efficiently, and at global scale. As demand for AI continues to grow, we are expanding the ways OpenAI can bring high-performance inference capacity online across a diverse hardware ecosystem. About the Team The GPT Infrastructure team builds software that turns advanced inference and optimization research into production products. One focus is enabling strategic infrastructure partners and accelerator vendors to qualify and onboard new compute without a bespoke porting and optimization effort for every hardware platform. We build the control planes, APIs, secure partner-side execution environments, evaluation systems, artifact pipelines, and operational tooling that make these workflows repeatable and trustworthy. The work sits at the intersection of distributed systems, AI inference, compilers and runtimes, performance engineering, security, and external partnerships. About the Role We are seeking an experienced systems generalist who can work comfortably across the stack to help build an automated inference optimization platform. Given a workload, target hardware profile, compiler and runtime context, and a trusted verifier, the system runs durable optimization campaigns that generate, compile, execute, grade, and improve candidate kernels, runtime configurations, and serving-stack changes. You will design both the OpenAI-hosted control plane and the partner-side software that evaluates candidates on real accelerator hardware. The product must keep long-running workflows reliable, make performance results reproducible, and maintain clear trust boundaries around sensitive model and hardware information. This is a deeply cross-stack role, combining strong software engineering fundamentals with systems thinking and

About the Team Our Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role We’re looking for a GPU Inference Engineer to contribute to improvements in model serving efficiency for our Robotics research. This is a high-impact role where you’ll drive initiatives to optimize inference performance and scalability. You’ll also be engaged in model design, to help assist our researchers in developing inference-friendly models. This role is critical to scaling the team’s broader goals - it will directly enable leadership to focus on higher-leverage initiatives by building a stronger technical foundation. In this role you will: Perform engineering efforts focused on improving model serving, inference performance, and system efficiency Drive optimizations from a kernel and data movement perspective to improve system throughput and reliability Partner closely with research and product teams to ensure our models perform effectively at scale Design, build, and improve critical serving infrastructure to support Robotics growth and reliability needs You might thrive in this role if you: Have deep expertise in model performance optimization, particularly at the inference layer Have a strong background in kernel-level systems, data movement, and low-level performance tuning Are excited about scaling high-performing AI systems that serve real-world, multimodal workloads Can navigate ambiguity, set technical direction, and drive complex initiatives to completion This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. About OpenAI OpenAI i

About the Team OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI. About the Role As an Engineer on our hardware optimization and co-design team, you will co-design future hardware from different vendors for programmability and performance. You will work with our kernel, compiler and machine learning engineers to understand their unique needs related to ML techniques, algorithms, numerical approximations, programming expressivity, and compiler optimizations. You will evangelize these constraints with various vendors to develop and influence future hardware architectures towards efficient training and inference on our models. If you are excited about efficiently distributing a large language model across devices, dealing with and optimizing system-wide/rack-wide networking bottlenecks and eventually tailoring the compute pipe and memory hierarchy of the hardware platform, simulating workloads at different abstractions and working closely with our partners, this is the perfect opportunity! This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. Key Responsibilities Co-design future hardware for programmability and performance with our hardware vendors Assist hardware vendors in developing optimal kernels and add support for it in our compiler Develop performance estimates for critical kernels for different hardware configurations and drive decisions on compute core and memory h

About the Team OpenAI’s Infrastructure organization builds and evaluates the systems that power advanced AI workloads. We work closely with hardware, modeling, and architecture teams to ensure that new platforms deliver real-world performance aligned with workload needs. Our team focuses on understanding workload behavior across evolving hardware platforms—bridging the gap between theoretical capability and observed system performance. About the Role We are seeking a Workload Porting & Performance Engineer to evaluate new hardware platforms by porting benchmarks and real-world workloads, analyzing performance, and identifying system bottlenecks. In this role, you will bring up workloads on new systems, characterize performance behavior, and adapt workloads to better utilize hardware capabilities. You will play a critical role in validating new platforms and ensuring that performance aligns with expectations across compute, memory, and networking subsystems. This role requires strong hands-on experience with performance analysis, workload optimization, and system-level debugging across hardware and software boundaries. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance. Key Responsibilities Port and enable benchmarks and real-world workloads on new hardware platforms. Evaluate system performance across compute, memory, storage, and networking subsystems. Identify and analyze performance bottlenecks and inefficiencies. Adapt and optimize workloads to better utilize hardware capabilities. Develop and run performance experiments and profiling workflows. Compare expected vs. observed performance and provide feedback to: hardware architecture teams performance modeling teams system and software engineers. Debug issues across the stack, including software, runtime, and hardware interactions. Provide actionable insights to guide platform readiness and deployment decisions. Qualifications E

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. The Identity & Access management (IAM) team’s charter is to enable our customers to confidently bring their most sensitive data and workloads to Snowflake. We provides the authentication and authorization capabilities for customers to secure their Snowflake accounts. We are heavily focused on critical AI adoption and security capabilities like Snowflake Intelligence access control, MCP server and clients, Agent identity, Admin guardrails for agents etc. Our feature set includes capabilities like user management, secret-less authentication for both human and service users, SSO integration with numerous IdPs, MFA, OAuth and OIDC support for 3P applications, and RBAC for granular access control. Our systems are critical to customer trust and maintaining Snowflake’s security, reliability and performance. The team culture is very collaborative with ample opportunities for growth and mentorship from Principal engineers. AS A SENIOR SOFTWARE ENGINEER - IDENTITY & ACCESS MANAGEMENT, YOU WILL: Design and implement critical AI security capabilities for controlled, audited, restricted agent workflows, both inbound and outbound. Design and implement features that provide critical identity and access management capabilities, including integration with the next generation identit

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Build the future of data. Join the Snowflake team. The Snowflake Machine Learning Platform team’s mission is to enable customers to bring their machine learning and deep learning workloads to Snowflake. Our customers want to build powerful models with the ever-increasing data in Snowflake but face several challenges including infrastructure optimizations, orchestration, performance, and security. The team aims to solve these challenges by building highly integrated platform solutions that are simple, secure, and enable end-to-end ML workflows. We are on an early journey to build the most scalable machine learning and data platform without sacrificing the benefits of a single platform and governance. We are looking for outstanding technical leaders who will join our ML Platform team to build the next-generation platform and play a pivotal role in this journey by understanding Snowflake’s core platform architecture and evolving it to enable state-of-the-art machine learning and LLM workloads. Join us to define strategies, set technical directions, design and execute, engage and deliver innovation, and unlock the power of AI for thousands of enterprise customers. This position is based in Menlo Park, CA, and Bellevue, WA. RESPONSIBILITIES : Help define and own the roadmap, wor

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in artificial intelligence possible! We do it all while committing to integrity, sustainability, and giving back to our communities, because doing so can fuel the very innovation we are pursuing. As a process integration engineer in the DRAM organization, you will be part of a team of world-class engineers who are working in an industry leading 300mm R&D facility on technology which enables future memory scaling. You will focus on the performance and manufacturability of Micron’s cutting-edge next-generation memories. Areas of concentration will include integration and circuit issues specific to DRAM technology. In addition to a broad basis of process integration knowledge, this position will require a strong background in semiconductor device physics. Role interacts significantly with the process development, simulation, modeling, characterization, and reliability groups. Responsibilities include, but not limited to: Lead technology integration activities in enabling manufacturability of state-of-the-art DRAM technology Engage with numerous cross-functional teams including process development, product engineering, design, yield improvement, advanced mask and probe to arrive at solutions to

Job Details: Job Description: The Role As a Cloud Application Development Engineer within Intel Manufacturing Foundry Cloud Services (imFCS) , you will design, develop, deploy, and support cloud-native applications that power semiconductor manufacturing, engineering automation, and AI-driven factory operations. You will build scalable, secure, and resilient platforms that improve engineering productivity, enable advanced analytics, and accelerate Intel Foundry's digital transformation. Key Responsibilities Develop and maintain cloud-native applications and services supporting manufacturing and engineering workflows. Support 24x7 manufacturing operations through on-call rotations, incident response, and root-cause analysis. Design and implement scalable microservices, APIs, and containerization systems utilizing Kubernetes orchestrator and cloud native applications. Architect secure cloud solutions spanning application, data, networking, identity, and observability domains. Build and maintain CI/CD pipelines, Infrastructure-as-Code, and DevOps automation. Provide technical leadership for contractor and partner development teams across multiple geographic regions, driving architecture, implementation, and operational excellence for cloud-native solutions. Collaborate with manufacturing, engineering, and software teams to deliv

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary The Senior Software Engineer / Technical Lead (AI & Automation) will provide technical leadership for the design, development, modernization, and support of critical applications supporting Prior Authorization Operations (PAOps) under PBM line of business. This role will be responsible for building and maintaining scalable, cloud-native solutions that enable intelligent workflow automation, AI-driven decisioning, document processing, and business process optimization. The ideal candidate is a hands-on technical leader with strong software engineering and cloud architecture expertise, coupled with practical experience implementing Generative AI, Agentic AI, and Large Language Model (LLM) solutions in production environments. This individual will collaborate closely with Data Engineering, Data Science, Product, and Business teams to deliver highly available, secure, and scalable applications while driving innovation through AI-powered solutions. Key areas of focus include: Application architecture, development, and production support Cloud-native engineering and platform modernization Microservices and distributed systems AI/GenAI, Agentic AI, and LLM-based solutions Event-driven and streaming architectures Engineering best practices, mentoring, and technical leadership R

What if the work you did every day could impact the lives of people you know? Or all of humanity? At Illumina, we are expanding access to genomic technology to realize health equity for billions of people around the world. Our efforts enable life-changing discoveries that are transforming human health through the early detection and diagnosis of diseases and new treatment options for patients. Working at Illumina means being part of something bigger than yourself. Every person, in every role, has the opportunity to make a difference. Surrounded by extraordinary people, inspiring leaders, and world changing projects, you will do more and become more than you ever thought possible. Our team specializes in developing a fast and accurate platform called DRAGEN for the secondary analysis of NGS genomic data. The platform covers a wide range of pipelines spanning germline and somatic analysis (WGS and targeted; tumor/normal and tumor-only), DNA and RNA workflows, and variant classes including small variants, CNVs, and structural variants. We are looking for a highly driven and talented Staff Bioinformatics Scientist to join our methods development team to work on secondary analysis algorithms. The ideal candidate will have a strong background in computer science, algorithms, statistics, or digital signal processing in addition to expertise in genomics and next generation sequencing. The candidate should be a proven team player and will contribute to the production software codebase. This role will focus on software development for structural variant detection, pangenome references, graph-based algorithms, and NGS assembly methods. Responsibilities: Design, prototype, and implement innovative computational or statistical algorithms to extract meaningful biological signal from sequencing assays. Im

Yext (NYSE: YEXT) is the enterprise agentic marketing platform. Built on the world's most comprehensive structured data platform for local businesses, Yext gives brands and their partners the visibility intelligence to win every moment of discovery – across AI and traditional search. Yext's API-first architecture connects structured data to APIs, MCP servers, and generative interfaces, so partners and developers can build purpose-built experiences on the same infrastructure powering Yext's own products. Thousands of brands and digital marketing partners in financial services, healthcare, retail, hospitality, and food rely on Yext to manage, measure, and optimize visibility at scale. For more information, visit yext.com . At Yext, Product Engineering builds and evolves the technology behind our products and services. We’re looking for software engineers who want to solve meaningful technical problems, contribute to systems at scale, and help shape what we build next. We work in an agile environment with two-week sprints and regular demos that keep teams aligned and give engineers clear visibility into the impact of their work. From day one, you’ll contribute directly to the codebase and collaborate with experienced engineers from a wide range of leading universities and technology companies. We are looking for an engineer to join Team Watson , which owns and develops the systems that power Yext Search and Yext Chat. The team builds the indexing, retrieval, and serving technology that enables brands to deliver fast, relevant answers across their websites and digital experiences. Yext Search handles more than 50 million requests each month, serving users around the world in over a dozen languages. Watson also brings these search and retrieval capabilities to Yext Chat, helping conversational experiences generate useful answers grounded in trusted customer content. Because Watson’s systems serve real-time, customer-facing experiences at a global scale, engineers o